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Mining of lattice distortion, strength, and intrinsic ductility of refractory high entropy alloys

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npj Computational Materials 2023年第1期9卷 1814-1825页

作者： Christopher Tandoc Yong-Jie Hu Liang Qi Peter K.Liaw Department of Materials Science and Engineering Drexel UniversityPhiladelphiaPA 19104USA Department of Materials Science and Engineering University of MichiganAnn ArborMI 48109USA Department of Materials Science and Engineering University of TennesseeKnoxvilleTN 37996USA

Severe lattice distortion is a prominent feature of high-entropy alloys(HEAs)considered a reason for many of those alloys’properties.Nevertheless,accurate characterizations of lattice distortion are still scarce to only cover a tiny fraction of HEA’s giant composition space due to the expensive experimental or computational costs.Here we present a physics-informed statistical model to efficiently produce high-throughput lattice distortion predictions for refractory non-dilute/high-entropy alloys(RHEAs)in a 10-element composition space.The model offers improved accuracy over conventional methods for fast estimates of lattice distortion by making predictions based on physical properties of interatomic bonding rather than atomic size mismatch of pure elements.The modeling of lattice distortion also implements a predictive model for yield strengths of RHEAs validated by various sets of experimental data.Combining our previous model on intrinsic ductility,a data mining design framework is demonstrated for efficient exploration of strong and ductile single-phase RHEAs.

关键词： alloys ductility strength

Osteoblast compatibility of 3D printed Co-Cr-Mo alloys with different building direction

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Biosurface and Biotribology 2019年第2期5卷 67-70页

作者： Satoshi Migita Kosuke Sakashita Suyalatu Graduate School of Science and Engineering Yamagata University4-3-16 JonanYonezawaYamagataJapan NTT Data Engineering Systems Corporation AM Design Lab 2-6-58 SenbahigashiMinooOsakaJapan

Three-dimensional(3D)metal printing is an attractive technique for fabricating biomedical devices.The microstructures and mechanical properties of the fabricated 3D metal printed products show anisotropy because the grains grow along the z-axis direction.However,the effects of different printing directions on the cytocompatibility of the products are unknown.In the present study,cobalt-chromium-molybdenum(Co-Cr-Mo)alloy cylinders were fabricated along the z-axis(vertical)and x-axis(horizontal),respectively,and the effect of build direction on the cytocompatibility was evaluated.The build direction of 3D printed Co-Cr-Mo alloy changed grain anisotropy;however,there was no statistical difference in grain size.The wettability,protein adsorption,cell attachment,and cell proliferation on the disks of vertical and horizontal products were similar to those on cast alloy;they were significantly lower than those of commercially pure titanium and tissue culture polystyrene.The build direction of 3D printed Co-Cr-Mo alloy does not affect osteoblast compatibility.

关键词： alloy grain alloys

A review on solidification of alloys under hypergravity

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Progress in Natural Science:Materials International 2023年第3期33卷 279-294页

作者： Fangjie You Xinbao Zhao Quanzhao Yue Yuefeng Gu Jiahui Wang Hongbin Bei Ze Zhang Institute of Superalloys Science and Technology School of Materials Science and Engineering Zhejiang University State Key Laboratory of Silicon and Advanced Semiconductor Materials Zhejiang University Polytechnic Institute Zhejiang University

A comprehensive and integrated review of the hypergravity field applied to solidifying alloys is provided. The hypergravity field refers to an environment in which the acceleration of gravity is more significant than the gravitational acceleration through rotation, resulting in significant changes in the solidification behavior of the alloy. The convection mode of the melt is closely related to the level and direction of hypergravity. Obvious floatation or sedimentation of solutes and crystals of different densities is induced. Columnar-to-equiaxed transition, grain refinement, and gradients in composition and microstructure are readily available under hypergravity. Furthermore, the nucleation and growth of crystals and their migration under enhanced convection are gradually revealed through simulations and in-situ observations. This review aims to summarize the universal law of the effect of the hypergravity field on the composition distribution and microstructure evolution of alloys during solidification. Based on the development of hypergravity equipment and characterization methods, it is expected to broaden the theoretical framework of hypergravity solidification. To provide a theoretical reference for developing new solidification processes and high-performance materials.

关键词： alloys Convection Grain refinement Hypergravity Segregation Solidification

Distilling physical origins of hardness in multi-principal element alloys directly from ensemble neural network models

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npj Computational Materials 2022年第1期8卷 1450-1460页

作者： D.Beniwal P.Singh S.Gupta M.J.Kramer D.D.Johnson P.K.Ray Metallurgical&Materials Engineering Indian Institute of Technology RoparRupnagar140001PunjabIndia Ames Laboratory US Department of EnergyAmesIA50011USA Materials Science&Engineering Iowa State UniversityAmesIA50011USA

Despite a plethora of data being generated on the mechanical behavior of multi-principal element alloys,a systematic assessment remains inaccessible via Edisonian approaches.We approach this challenge by considering the specific case of alloy hardness,and present a machine-learning framework that captures the essential physical features contributing to hardness and allows high-throughput exploration of multi-dimensional compositional space.The model,tested on diverse datasets,was used to explore and successfully predict hardness in Al_(x)Ti_(y)(CrFeNi)_(1-x-y),Hf_(x)Co_(y)(CrFeNi)_(1-x-y)and Al_(x)(TiZrHf)_(1-x)systems supported by data from density-functional theory predicted phase stability and ordering behavior.The experimental validation of hardness was done on TiZrHfAlx.The selected systems pose diverse challenges due to the presence of ordering and clustering pairs,as well as vacancy-stabilized novel structures.We also present a detailed model analysis that integrates local partial-dependencies with a compositional-stimulus and model-response study to derive material-specific insights from the decision-making process.

关键词： alloys alloy element

Composition design of high-entropy alloys with deep sets learning

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npj Computational Materials 2022年第1期8卷 834-844页

作者： Jie Zhang Chen Cai George Kim Yusu Wang Wei Chen Department of Mechanical Materialsand Aerospace EngineeringIllinois Institute of TechnologyChicagoIL60616USA Halıcıoğlu Data Science Institute University of California San DiegoLa JollaCA92093USA

High entropy alloys(HEAs)are an important material class in the development of next-generation structural materials,but the astronomically large composition space cannot be efficiently explored by experiments or first-principles calculations.Machine learning(ML)methods might address this challenge,but ML of HEAs has been hindered by the scarcity of HEA property data.In this work,the EMTO-CPA method was used to generate a large HEA dataset(spanning a composition space of 14 elements)containing 7086 cubic HEA structures with structural properties,1911 of which have the complete elastic tensor calculated.The elastic property dataset was used to train a ML model with the Deep Sets architecture.The Deep Sets model has better predictive performance and generalizability compared to other ML models.Association rule mining was applied to the model predictions to describe the compositional dependence of HEA elastic properties and to demonstrate the potential for data-driven alloy design.

关键词： alloys alloy entropy

Emergence of local scaling relations in adsorption energies on high-entropy alloys

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npj Computational Materials 2022年第1期8卷 815-821页

作者： Wissam A.Saidi National Energy Technology Laboratory United States Department of EnergyPittsburghPA15236USA Department of Mechanical Engineering and Materials Science University of PittsburghPittsburghPA15261USA

Alloying has been proposed to circumvent scaling relations between the adsorption energies thus allowing for the complete optimization of multistep reactions.Herein the fidelity of scaling rules on high-entropy alloy(HEA)surfaces is assessed focusing on hydrogen-containing molecules,^(*)AH_(x) for A=C and N(x=0,1,2,3),A=S(x=0,1,2)and A=O(x=0,1).Using an adsorbate-and site-specific deep learning model to rapidly compute the adsorption energies on CoMoFeNiCu HEA surfaces,the energies of ^(*)AH_(x) and ^(*)A are shown to be linearly correlated if ^(*)A and ^(*)AH_(x) have identical adsorption site symmetry.However,a local linear dependence emerges between the configuration-averaged adsorption energies irrespective of the site symmetry.Although these correlations represent a weaker form of the scaling relationships,they are sufficient to prohibit the optimization of multistep reactions.The underpinning of this behavior is twofold(1)the nearsightedness principle and(2)the narrow distribution of the adsorption energies around the mean-field value.While the nearsightedness is general for all electronic systems,the second criterion applies in HEAs with relatively strong reactive elements.The present findings strongly suggest that alloys may not generally enable the breaking of scaling relationships.

关键词： alloys alloy adsorption

Element-wise representations with ECNet for material property prediction and applications in high-entropy alloys

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npj Computational Materials 2022年第1期8卷 2409-2418页

作者： Xinming Wang Nguyen-Dung Tran Shuming Zeng Cong Hou Ying Chen Jun Ni State Key Laboratory of Low-Dimensional Quantum Physics Department of PhysicsTsinghua UniversityBeijing100084China Frontier Science Center for Quantum Information Beijing100084China Fracture and Reliability Research Institute School of EngineeringTohoku University6-6-01 AramakiaobaAobakuSendai980-8579Japan College of Physics Science and Technology Yangzhou UniversityYangzhou225002China Collaborative Innovation Center of Quantum Matter Beijing100084China

When developing deep learning models for accurate property prediction,it is sometimes overlooked that some material physical properties are insensitive to the local atomic environment.Here,we propose the elemental convolution neural networks(ECNet)to obtain more general and global element-wise representations to accurately model material properties.It shows better prediction in properties like band gaps,refractive index,and elastic moduli of crystals.To explore its application on high-entropy alloys(HEAs),we focus on the FeNiCoCrMn/Pd systems based on the data of DFT calculation.The knowledge from less-principal element alloys can enhance performance in HEAs by transfer learning technique.Besides,the element-wise features from the parent model as universal descriptors retain good accuracy at small data limits.Using this framework,we obtain the concentration-dependent formation energy,magnetic moment and local displacement in some sub-ternary and quinary systems.The results enriched the physics of those high-entropy alloys.

关键词： alloys prediction entropy

Electronic structure factors and the importance of adsorbate effects in chemisorption on surface alloys

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npj Computational Materials 2022年第1期8卷 1560-1571页

作者： Shikha Saini Joakim Halldin Stenlid Frank Abild-Pedersen SUNCAT Center for Interface Science and Catalysis Department of Chemical EngineeringStanford University443 Via OrtegaStanfordCA94305USA SUNCAT Center for Interface Science and Catalysis SLAC National Accelerator Laboratory2575 Sand Hill RoadMenlo ParkCA94025USA

The chemisorption energy is an integral aspect of surface chemistry,central to numerous fields such as catalysis,corrosion,and nanotechnology.Electronic-structure-based methods such as the Newns-Anderson model are therefore of great importance in guiding the engineering of material surfaces with optimal properties.However,existing methods are inadequate for interpreting complex,multi-metallic systems.Herein,we introduce a physics-based chemisorption model for alloyed transition metal surfaces employing primarily metal d-band properties that accounts for perturbations in both the substrate and adsorbate electronic states upon interaction.Importantly,we show that adsorbate-induced changes in the adsorption site interact with its chemical environment leading to a second-order response in chemisorption energy with the d-filling of the neighboring atoms.We demonstrate the robustness of the model on a wide range of transition metal alloys with O,N,CH,and Li adsorbates yielding a mean absolute error of 0.13 eV versus density functional theory reference chemisorption energies.

关键词： alloys corrosion chemisorption

Review on ω Phase in Body-Centered Cubic Metals and alloys

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Acta Metallurgica Sinica(English Letters) 2014年第1期27卷 1-11页

作者： Dehai Ping National Institute for Materials Science Sengen 1-2-1Tsukuba 305-0047Japan

An ω phase with a primitive hexagonal crystal structure has been found to be a ωmmon metastable phase in body-centered cubic （bcc） metals and alloys. In general, ω phase precipitates out as a high density of nanoscale particles and can obviously strengthen the alloys; however, ωarsening of the ω particles significantly reduces the alloy ductility. The ω phase has ωherent interfacial structure with its bcc matrix phase, and its lattice parameters are aω ---- x/2 x abcc and ωbcc= v/3/2 abcc abet. The ωmmon { 112} （111）-type twinning in bcc metals and alloys can be treated as the product of the ω ~ bcc phase transition, also known as the ω-lattice mechanism. The ω phase＇s behavior in metastable 13-type Ti alloys will be briefly reviewed first since the ω phase was first found in the alloy system, and then the existence of the ω phase in carbon steels will be discussed. Carbon plays a crucial role in promoting the ω formation in steel, and the ω phase can form a solid solution with various carbon ωntents. Hence, the martensitic substructure can be treated as an ct-Fe matrix embedded with a high density of nanoscale ω-Fe particles enriched with carbon. The reωgnition of the ω phase in steel is expected to advance the understanding of the relationship between the microstructure and mechanical properties in bcc steels, as well as the behavior of martensitic transformations, twinning formation, and martensitic substructure.

关键词： ω phase Martensitic steel Microstructure Microanalysis bcc metals alloys Twinning